This invention relates to the monitoring of drug development studies, such as phase III drug development studies, for adverse effects, and more particularly, to a system for detecting when the number of adverse effects becomes excessive.
Phase III of a clinical development program involves the large-scale application of the new drug to patients (the desired effect of the drug is evaluated in phase II). The aim of a phase III study is to confirm the efficacy of the recommended dose of the final formulation and to evaluate the risk of adverse events. Adverse events can include those that are expected from observations made during earlier study work on the drug, as well as those adverse events which are unexpected. Typically, the studies in this phase are double-blind comparisons of the new drug versus a control, which is a placebo, or, alternatively, the best existing product. In this phase, many new side-effects are detected. Phase III studies are performed in order to assess the risk of frequent adverse events.
It may be necessary to close the project if too many patients experience adverse events, particularly if they are serious adverse events. The risk of rare and severe adverse events cannot be assessed with sufficient precision, but the events must be monitored in order to stop the trials if there is a major safety problem.
Although studies of this type can involve thousands of patients, such studies may nevertheless be underpowered for evaluating the more serious and rare events. However, there still is a need to monitor these events, and if they are too frequent, the drug development program needs to be stopped.
Typically, in these studies there is an expedited reporting system allowing the clinical centers to report serious adverse events to a drug company safety officer, who in turn may report such events to the authorities. Additionally, there might be a safety committee to initiate a detailed examination of suspected side effects, and to take decisions and/or make recommendations to the management, in case drug safety is compromised.
The standard safety measures are, however, not satisfactory because they have few formal methods to base their decisions upon. One reason for this is that at least some types of adverse events may be unexpected, and some sort of categorization of diagnoses is needed. Another reason is the blind nature of phase III testing. Technically, it would be preferable to include all patients accounting for the actual treatment, but this might lead to suspicions on the integrity of the blinding of the studies. Furthermore, this approach may not be practical, because the data flow for patients not suffering from the adverse events is markedly slower. A third difficulty is the sequential nature of the problem, making statistical methods intrinsically more complicated.
Examples of surveillance systems for monitoring health-related programs include: Chen, R., xe2x80x9cA Surveillance System For Congenital Malformationsxe2x80x9d, J. Am. Statist. Assoc. 1978; 73: 323-327; Gallus, G., et al. xe2x80x9cOn Surveillance Methods For Congenital Malformationsxe2x80x9d, Statist. Med. 1986; 5: 565-571; Lie, R.T., et al., xe2x80x9cA New Sequential Procedure For Surveillance of Down""s Syndromexe2x80x9d, Statist. Med. 1993; 12: 13-25. These references describe systems for monitoring birth defects, and they provide that after an alarm has occurred, action such as a warning requiring a detailed investigation be taken. These papers study an overall response, that is, observations are not split in subgroups, like treatment.
Other references of general interest include Lucas, J. M. xe2x80x9cCounted Data CUSUM""sxe2x80x9d, Technometrics, 1985; 27: 129-144; Brook, D., et al. xe2x80x9cAn Approach to the Probability Distribution of CUSUM Run Lengthxe2x80x9d, Biometrika 1972; 59: 539-549; and Wald, A., xe2x80x9cSequential Analysisxe2x80x9d, New York: John Wiley and Sons; 1947.
Another article of interest is Bolland, et al. xe2x80x9cFormal Approaches to Safety Monitoring of Clinical Trials in Life-Threatening Conditionsxe2x80x9d, Statist. Med. 2000; 19:2899-2917. This paper describes the application of a binomial sequential test among deaths in a clinical trial; comparing the proportion with xc2xd, the proportion of patients randomized to the experimental treatment.
Surveillance of tests such as phase III trials is important to insure the overall health of the many patients involved, the concerns of the doctors and authorities involved, and the substantial time and expense of such testing. Monitoring of trials is also important to reduce the likelihood of the administering drug company being sued if there is a problem.
No satisfactory approach for the clinical surveillance of testing programs was found in the literature.
A new, simple approach to surveillance of adverse events, and more particularly, serious adverse events, during phase III is suggested (phase III studies are typically double blind comparisons of the drug with placebo, or a control, performed in order to assess the risk of frequent adverse events).
Although the present invention is described in the context of a phase III study, this invention is not to be limited thereto. It should be understood that, given the teachings in this application, those skilled in the art would understand the present invention also is applicable to other parts of drug development studies such as Phase II and IV, and even to other types of studies.
The present invention provides for the expedited reporting of adverse events, and such reporting can involve the entity administering the testing, and/or the authorities.
Although this invention is phrased in terms of serious adverse events, it also relates to the monitoring of other adverse events. Those skilled in the art will understand that the same procedures could be used for both serious and other adverse events, and so the use herein of one or the other of those expressions should be understood to encompass both types of events.
The present invention involves a CUSUM approach, where the events in the treatment group are cumulated, adjusting for the expected numbers based on the total number of adverse events. Thus, if there are many events in the treatment group compared to the control group, there will be an xe2x80x9calarmxe2x80x9d. In response, the procedure xe2x80x9cunblindsxe2x80x9d the treatment for serious adverse events, but no other information is revealed from the ongoing studies.
The exact probability properties of this sequential Bernoulli procedure can be evaluated by means of Markov chain methods. Optimizing the surveillance program with respect to the mean time to alarm (the standard in CUSUM applications) leads to a design that depends on the alternative considered, whereas the optimum solution based on the probability of alarm within the expected course of the study is independent of the alternative.
The procedure was applied to adverse events for a drug known as NNC 46-0020, a partial estrogen receptor agonist. A finding of too many adverse events led to closure of the product.